Advancing Strongyloides Omics Data: Bridging the Gap with Caenorhabditis elegans

Reem Al-Jawabreh; Dominika Lastik; Darrin McKenzie; Kieran Reynolds; Mona Suleiman; Angela Mousley; Louise Atkinson; Vicky Hunt

doi:10.1098/rstb.2022.0437

Advancing Strongyloides Omics Data: Bridging the Gap with Caenorhabditis elegans

Reem Al-Jawabreh, Dominika Lastik, Darrin McKenzie, Kieran Reynolds, Mona Suleiman, Angela Mousley, Louise Atkinson, Vicky Hunt

Queen's University Belfast

Research output: Contribution to journal › Review article › peer-review

2 Citations (SciVal)

Abstract

Among nematodes, the free-living model organism Caenorhabditis elegans boasts the most advanced portfolio of high-quality omics data. The resources available for parasitic nematodes, including Strongyloides spp., however, are lagging behind. While C. elegans remains the most tractable nematode and has significantly advanced our understanding of many facets of nematode biology, C. elegans is not suitable as a surrogate system for the study of parasitism and it is important that we improve the omics resources available for parasitic nematode species. Here, we review the omics data available for Strongyloides spp. and compare the available resources to those for C. elegans and other parasitic nematodes. The advancements in C. elegans omics offer a blueprint for improving omics-led research in Strongyloides. We suggest areas of priority for future research that will pave the way for expansions in omics resources and technologies. This article is part of the Theo Murphy meeting issue 'Strongyloides: omics to worm-free populations'.

Original language	English
Article number	20220437
Number of pages	22
Journal	Philosophical Transactions of the Royal Society B: Biological Sciences
Volume	379
Issue number	1894
Early online date	27 Nov 2023
DOIs	https://doi.org/10.1098/rstb.2022.0437
Publication status	Published - 15 Jan 2024

Bibliographical note

Funding Information:
This work was supported by Biotechnology and Biological Sciences Research Council-funded South West Biosciences Doctoral Training Partnership (grant no. BB/T008741/1) awarded to R.A.-J., the Department of Agriculture, Environment and Rural Affairs (DAERA) studentship awarded to D.M., GW4 BIOMED MRC DTP (MR/W006308/1) awarded to K.R., University of Bath Research Studentship Award to M.S., Academy of Medical Sciences Springboard Award (grant no. SBF004\1018) to L.A., Biotechnology and Biological Sciences Research Council (grant no. BB/T016396/1) award to A.M. and a Wellcome Trust Sir Henry Dale Fellowship (211227/Z/18/Z) awarded to V.H.

Keywords

genomics
proteomics
small RNA
Strongyloides
transcriptomics
transposable elements

ASJC Scopus subject areas

General Biochemistry,Genetics and Molecular Biology
General Agricultural and Biological Sciences

Access to Document

10.1098/rstb.2022.0437Licence: CC BY

Cite this

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abstract = "Among nematodes, the free-living model organism Caenorhabditis elegans boasts the most advanced portfolio of high-quality omics data. The resources available for parasitic nematodes, including Strongyloides spp., however, are lagging behind. While C. elegans remains the most tractable nematode and has significantly advanced our understanding of many facets of nematode biology, C. elegans is not suitable as a surrogate system for the study of parasitism and it is important that we improve the omics resources available for parasitic nematode species. Here, we review the omics data available for Strongyloides spp. and compare the available resources to those for C. elegans and other parasitic nematodes. The advancements in C. elegans omics offer a blueprint for improving omics-led research in Strongyloides. We suggest areas of priority for future research that will pave the way for expansions in omics resources and technologies. This article is part of the Theo Murphy meeting issue 'Strongyloides: omics to worm-free populations'.",

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Advancing Strongyloides Omics Data: Bridging the Gap with Caenorhabditis elegans

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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